While it might be tempting to liven up a report or presentation with a few 3D graphs, two-dimensional representation is generally better when numbers are the primary information you want to communicate. Nevertheless, on occasions when numeric values aren’t the primary focus, and you’re more interested in showing the shape of the data, adding a...
Interaction Design for Data Exploration Visualizations capable of launching detail views can add value to a data analyst’s user experience. Programming in this kind of interaction automates the creation of complementary charts and increases ease of exploration by linking varied views of the data in a logical way.
Imagine someone were to mint a new coin and give it to you. You then buy something and give it to someone else, and so on. Every time this coin changes hands, a record of the transaction is engraved on the coin. Every transaction in the history of that coin’s existence is in plain sight on the face of the coin—and the longer the coin...
Applying Regular Expressions This is a tutorial on processing data with regular expressions using Python. It is also a reflection on the advantages and trade-offs that come into play when you use regular expressions. Once you have identified and defined a set of patterns, you can strategically search and extract data from raw text according...
Our team recently designed a dashboard using R Shiny Leaflet allowing users to select many locations at one go on an interactive map. We created the map using the package leaflet.extras, which enables users to draw shapes on R Shiny Leaflet maps. When combined with the package sp and a function called findLocations, the leaflet.extras drawing...